Latest AI and machine learning research in covid-19 for healthcare professionals.
Fast Magnetic Resonance Imaging (MRI) reconstruction on undersampled k-space data accelerates MRI scans while maintaining image quality. This enables faster diagnostics and improves patient comfort. Existing techniques face several challenges, including image artifacts, long reconstruction times, overfitting, and limited generalization across different anatomies or scan settings. These remain sign...
BACKGROUND: Donor-specific antibodies (DSA) against human leukocyte antigens (HLA) are associated with increased immunologic risk in kidney transplant recipients (KTR). However, outcomes among DSA-positive patients are highly variable. Traditional markers, such as DSA class and mean fluorescence intensity (MFI), often fail to capture the multidimensional nature of immunologic risk. AIM: This retro...
BACKGROUND: Egypt's health financing is characterised by persistently high out-of-pocket (OOP) payments exceeding 50% of total health expenditure and ...
Lyme disease, the most common tick-borne infectious disease in the United States, presents with highly variable clinical outcomes, ranging from locali...
Thrombosis remains a major cause of morbidity and mortality in patients with cancer. Existing risk models fail to reliably predict venous thromboembol...
BACKGROUND: Preoperative cardiovascular risk stratification is essential in noncardiac surgery, but conventional testing is frequently overused, incre...
BACKGROUND: Response evaluation in pleural mesothelioma is challenging because its crescent growth pattern is poorly captured by diameter-based criter...
BACKGROUND: Membranous nephropathy (MN) is an autoimmune disease characterized by immune complex deposition and progressive renal function impairment....
Large language models have shown remarkable performance on medical examinations, but their application in oral and maxillofacial surgery remains under...
This study examines the pivotal role of artificial intelligence (AI) in advancing the urban green transition (UGT), with a particular focus on the Yan...
Accurate automated segmentation of Lumbar Spine Structures (LSS) in Magnetic Resonance Imaging (MRI) is important for effective diagnosis and treatmen...
There have been a few recent works showing the advantages of combining cell-free protein expression (CFE) with biolayer interferometry (BLI) for the r...
PURPOSE: To develop a deep learning model based on nnU-Net for automated segmentation of all perigastric veins on contrast-enhanced CT images in patie...
Identification of body fluid origin at crime scenes can help establish a link between the individual who sheds the sample and the criminal activity, t...
PURPOSE: Human calmodulin-1 (CaM) undergoes calcium-dependent conformational changes that are difficult to capture owing to substantial structural fle...
Liver tumor segmentation from CT images remains challenging due to large variations in lesion scale, blurred boundaries, low tissue contrast, and the ...
Identifying tumor-specific T-cell antigens is essential for advancing cancer immunotherapy and enabling precision-driven, AI-assisted discovery. While...
BACKGROUND: Laboratory testing is a cornerstone of diagnostic decision-making in emergency departments (EDs), yet its overuse contributes substantiall...
IgA nephropathy (IgAN) is the most prevalent primary glomerulonephritis worldwide. Although optimized supportive therapy is administered to these pati...
Automated seizure detection from long-term scalp electroencephalography (EEG) remains challenging because seizure windows are sparse, channel configur...